NDLI: Intel realsense = Real low cost gaze

Content Provider	IEEE Xplore Digital Library
Author	Draelos, M. Qiang Qiu Bronstein, A. Sapiro, G.
Copyright Year	2015
Description	Author affiliation: Duke Univ., Durham, NC, USA (Draelos, M.; Qiang Qiu; Sapiro, G.) \|\| Tel Aviv Univ., Ramat Aviv, Israel (Bronstein, A.)
Abstract	Intel's newly-announced low-cost RealSense 3D camera claims significantly better precision than other currently available low-cost platforms and is expected to become ubiquitous in laptops and mobile devices starting this year. In this paper, we demonstrate for the first time that the RealSense camera can be easily converted into a real low-cost gaze tracker. Gaze has become increasingly relevant as an input for human-computer interaction due to its association with attention. It is also critical in clinical mental health diagnosis. We present a novel 3D gaze and fixation tracker based on the eye surface geometry captured with the RealSense 3D camera. First, eye surface 3D point clouds are segmented to extract the pupil center and iris using registered infrared images. With non-ellipsoid eye surface and single fixation point assumptions, pupil centers and iris normal vectors are used to first estimate gaze (for each eye), and then a single fixation point for both eyes simultaneously using a RANSAC-based approach. With a simple learned bias field correction model, the fixation tracker demonstrates mean error of approximately 1 cm at 20-30 cm, which is sufficiently adequate for gaze and fixation tracking in human-computer interaction and mental health diagnosis applications.
Starting Page	2520
Ending Page	2524
File Size	984689
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Iris Cameras Estimation Active contours Geometry Image segmentation human-computer interaction gaze tracker fixation tracker depth camera mental health
Content Type	Text
Resource Type	Article

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